{"id":"W2979173459","doi":"10.1016/j.carbpol.2019.115429","title":"Facile preparation of collagen fiber–glycerol-carboxymethyl cellulose composite film by immersing method","year":2019,"lang":"en","type":"article","venue":"Carbohydrate Polymers","topic":"Collagen: Extraction and Characterization","field":"Materials Science","cited_by":51,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"National Key Research and Development Program of China; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Glycerol; Carboxymethyl cellulose; Aqueous solution; Ultimate tensile strength; Materials science; Composite number; Cellulose; Swelling; Adsorption; Chemical engineering; Thermostability; Composite material; Polymer chemistry; Chemistry; Nuclear chemistry; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003277374,0.0002376145,0.0003670621,0.0001492889,0.0001035596,0.00009857935,0.0002134258,0.0001538529,0.006006327],"category_scores_gemma":[0.0000169432,0.000251629,0.0001164273,0.0004427365,0.00006480125,0.0003978175,0.00006109594,0.00007177758,0.000533668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001049742,"about_ca_system_score_gemma":0.0000970227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002302459,"about_ca_topic_score_gemma":0.00000469387,"domain_scores_codex":[0.9980652,0.0002721194,0.0004981952,0.0004693429,0.0003610007,0.0003341377],"domain_scores_gemma":[0.9988689,0.0001114981,0.0004068264,0.0003717207,0.0001056943,0.0001353449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001711726,0.00005465168,0.00006597393,0.00004173051,0.00002258286,0.000001478965,0.0008367261,0.0006422698,0.9964476,0.0000290149,0.0006652157,0.001021588],"study_design_scores_gemma":[0.0005091444,0.000109559,0.0001528632,0.0000250696,0.00005348664,0.000003523003,0.0002733804,0.008806909,0.984728,0.000006255236,0.005067322,0.0002644377],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9876986,0.000319908,0.001830861,0.0001246996,0.0009256426,0.0004913142,0.0001692422,0.00008982395,0.008349869],"genre_scores_gemma":[0.9890604,0.00001900215,0.000747978,0.0001472699,0.00005020778,0.00002165,0.0002092066,0.00003370893,0.009710598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01171954,"threshold_uncertainty_score":0.9999936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009394683369796267,"score_gpt":0.2641241712111611,"score_spread":0.2547294878413648,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}